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Software Cost Estimation for the LADEE Mission Software Cost Estimation for the LADEE Mission Howard Cannon Karen Gundy-Burlet Intelligent Systems Division Intelligent Systems Division NASA-Ames Research Center NASA-Ames Research Center Moffett Field, CA 94035 Moffett Field, CA 94035 [email protected] [email protected] Abstract—The purpose of the Lunar Atmosphere Dust Environment Explorer (LADEE) mission was to measure the density, composition and time variability of the lunar dust I. INTRODUCTION environment. The ground-support and onboard flight software for the mission was developed using a “Model-Based Software” The Lunar Atmosphere Dust Environment Explorer (LADEE) methodology. In this technique, models of the spacecraft and [1] was a small NASA explorer class mission that launched flight software are developed in a graphical dynamics modeling September 6 of 2013 and was successfully deorbited on April package. Flight Software requirements are prototyped and 18, 2014. It orbited the moon to determine the density, refined using the simulated models. After the model is shown to composition and variability of the lunar exosphere. To work as desired in this simulation framework, C-code software is minimize fabrication and design costs, the “modular common automatically generated from the models. The auto-generated bus” spacecraft was designed with common structural code is then integrated with the Core Flight Executive and Core components that could be connected together to form the Flight Services (cFE/cFS) packages, VxWorks and appropriate spacecraft. LADEE was formed of four such modules, board support packages. The generated software is then tested in real time Processor-in-the-Loop and Hardware-in-the-Loop test housing the propulsion, avionics and three instruments for beds. observation of the moon. Software cost estimation for the mission was performed 3 ways: LADEE’s physical construction proceeded down a low-cost 1) Extrapolated from development of a earth-based prototype rapidly prototyped product-line effort, and a similar hover-test vehicle, 2) Estimated through the Goddard Space philosophy drove the development of the software base. With Flight Center “mission design center” 3) Through the use of strict launch deadlines, budget limitations and a short 100-day COCOMO based estimation spreadsheets. In this paper, we will mission plan, the flight software team surveyed successful discuss the characteristics of each of the cost estimation methods, examples of rapidly deployed small-spacecraft missions to and how they were tuned for a model-based development effort discover best practices. Of these, the AFRL XSS-10 and XSS- rather than a traditional effort. The estimates are also compared with actual costing and trend data for the LADEE Flight 11 spacecraft utilized model-based development Software effort. methodologies, and we proceeded with a trade study between modeling languages using a hover test vehicle [2]. One Keywords—software cost estimation, model-based software advantage with model-based development is that controls development engineers are able to rapidly prototype algorithms in their “native language” and software engineers could directly auto- TABLE OF CONTENTS code the models. This minimizes the opportunity for I. Introduction ...................................................... 1 communication errors between algorithm designers and qualified software developers. The model based-methodology II. Software Architecture ................................... 2 also enhances early prototyping of requirements, enables validation and verification during early stages of development III. Software Development Process ............... 3 and provides a common platform for communication between subsystems, software engineers and stakeholders. IV. Software Size Estimation ............................ 3 V. COCOMO Based Effort Estimation ............. 4 One difficulty with Model Based software development is that while there were anecdotal cases like XSS-10/11, there was VI. Bottoms up level of effort ........................... 5 limited literature on how to modify cost estimation to take into account the reputed savings of the technique. An additional VII. IMDC efffort ................................................... 6 factor in uncertainty of the mission cost was the background of the team: experienced software, systems and GN&C VIII. Results and Discussion ............................. 7 researchers and engineers, but without prior experience in IX. Conclusions ..................................................... 7 developing onboard flight software for spacecraft. To minimize budget risk, we researched best practices in cost References ................................................................. 8 estimation, and found extensive literature on cost estimation U.S. Government work not protected by U.S. copyright. 1 techniques [3]. We utilized three different cost estimation VxWorks [7] and a Board Support Package (BSP) for the techniques, including model based parametric techniques, BroadReach Integrated Avionics Unit (IAU). The BSP was expert judgment estimation and analogy from internal customized to be compliant with the Portable Operating prototyping efforts. System Interface (POSIX) standard defined by the IEEE Standards Association [8]. II. SOFTWARE ARCHITECTURE For the LADEE mission, the flight software was developed Figure 1 shows the integrated architecture for the LADEE utilizing a technique known as “Model-Based Software mission. The yellow circles indicate control functions that Development.” In this technique, models of the spacecraft and were developed in Simulink and auto-coded for integration high-level flight control software are developed in a graphical with the other elements. Blue circles indicate the tasks that modeling language, such as Mathworks’ Simulink [4]. Flight were reused from the cFS package. While the cFS code was Software requirements are prototyped, refined and partially wholly reused, the tasks were customized for the LADEE verified using the simulated models. After the model is shown spacecraft through modifications to tables and headers. The to work as desired in this simulation framework, “C”-code circles in green represent tasks that were newly developed software is automatically generated from the models. A hand-code, including hardware drivers for all sensors, Simulink Interface Layer then wraps the auto-generated code actuators and payloads as well as commanding, telemetry and to communicate across the bus with the Core Flight Executive memory scrub functions. The modules communicate across (cFE), Core Flight Software (cFS) and Operating System the bus using the cFE “publish/subscribe” paradigm. A Abstraction Layer (OSAL) [5,6] GOTS components feature of the LADEE software is the implementation of developed at NASA GSFC. These are then layered on POSIX standards within the device driver layers. FSW Architecture OFSW Cmd Attitude Thermal Power Battery Actuator State Safe Mode & Mode Control Control Control Charge Manager Estimator Controller Processor System System System System Software Bus Stored Memory Memory Limit House- Memory Hardware Scheduler Commands Manager Dwell Checker keeping Scrub I/O Health & File CCSDS File Data Telemetry Command Checksum Safety Manager Delivery Storage Output Ingest System Support and O/S Services Telemetry KEY Gnd Cmds Hdwr Cmds FSW Internal Hand Simulink cFS Sensor Data Written FSW External Task Task Task GSFC OSAL, cFE, cFS, ITOS (GOTS) Broad Reach Drivers (MOTS) Simulink/Matlab, VxWorks (COTS) 8 Figure 1 Flight Software Architecture 2 Figure 2 Agile Software Development Process IV. SOFTWARE SIZE ESTIMATION A key component of parametric cost estimation is an estimate III. SOFTWARE DEVELOPMENT PROCESS of Source Lines of Code (SLOC). LADEE utilized the NASA Key to the software estimation effort was the implementation Marshall (MSFC) “Source Lines of Code Estimator” of the agile model-based software development process shown spreadsheet, which quantifies source lines of code to be in Figure 2. For LADEE, the model based development developed given adjective descriptions of the size and effort using the Workstation Simulation (WSIM) environment complexity of the unit. An image of the detailed results from allowed early verification that the algorithms and software the spreadsheet is provided in Table 2. Comparing the design met the detailed control requirements. Software would software architecture in Figure 1 to the categories in the then be generated in the “C” programming language, and then SLOC spreadsheet reveals that the LADEE architecture did integrated with the other software layers and tested in real not map one-to-one with the general categories in the MSFC time Processor-in-the-Loop (PIL) and Hardware-in-the-Loop spreadsheet. For instance, The Safe Mode Controller (SMC), (HIL) environments. One HIL test-bed was denoted the and Attitude Control System (ACS) both map into “Attitude “Travelling Road Show”, and could be taken to payload Control” and “Gyro Package Management”, but “Sun development sites so that early integration testing could be Sensing” is part of the SMC system alone. The State performed. Once the data was generated from all of the Estimation Module (EST) has aspects of “Star Tracker”, various test-beds, it would be integrated into an automated “Attitude Determination”. Other systems map more closely, reporting system that provided bidirectional traceability such as Command Ingest (CI) and Telemetry Output (TO) between requirements,
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